Towards Viable Intrusion Detection Methods For The Automotive Controller Area Network

Andrew John Tomlinson; Jeremy Bryans; Siraj Shaikh

doi:10.1145/3273946.3273950

Towards Viable Intrusion Detection Methods For The Automotive Controller Area Network

Andrew John Tomlinson, Jeremy Bryans, Siraj Shaikh

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review

Abstract

The Controller Area Network (CAN) in cars is critical to their safety and performance and is now regarded as being vulnerable to cyberattack. Recent studies have looked at securing the CAN and at intrusion detection methods so that attacks can be quickly identified. The CAN has qualities that distinguish it from other computer networks, while the nature of car production and usage also provide challenges. Thus attach detection methods employed for other networks lack appropriateness for the CAN. This paper surveys the methods that have been investigated for CAN intrusion detection, and considers their implications in terms of practicability and requirements. Consequent developments that will be needed for implementation and research are suggested.

Original language	English
Title of host publication	2nd Computer Science in Cars Symposium - Future Challenges in Artificial Intelligence Security for Autonomous Vehicles (CSCS 2018)
Publisher	ACM
Number of pages	9
ISBN (Print)	978-1-4503-6616-8
DOIs	https://doi.org/10.1145/3273946.3273950
Publication status	Published - 13 Sept 2018
Event	ACM Computer Science in Cars Symposium: Future Challenges in Artificial Intelligence & Security for Autonomous Vehicles - Munich, Germany Duration: 13 Sept 2018 → 14 Sept 2018

Conference

Conference	ACM Computer Science in Cars Symposium
Abbreviated title	CSCS 2018
Country/Territory	Germany
City	Munich
Period	13/09/18 → 14/09/18

Keywords

intrusion detection, controller area network, automotive cybersecurity

Access to Document

10.1145/3273946.3273950

Cite this

Towards Viable Intrusion Detection Methods For The Automotive Controller Area Network. / Tomlinson, Andrew John; Bryans, Jeremy; Shaikh, Siraj.
2nd Computer Science in Cars Symposium - Future Challenges in Artificial Intelligence Security for Autonomous Vehicles (CSCS 2018). ACM, 2018.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review

Tomlinson, AJ, Bryans, J & Shaikh, S 2018, Towards Viable Intrusion Detection Methods For The Automotive Controller Area Network. in 2nd Computer Science in Cars Symposium - Future Challenges in Artificial Intelligence Security for Autonomous Vehicles (CSCS 2018). ACM, ACM Computer Science in Cars Symposium, Munich, Germany, 13/09/18. https://doi.org/10.1145/3273946.3273950

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abstract = "The Controller Area Network (CAN) in cars is critical to their safety and performance and is now regarded as being vulnerable to cyberattack. Recent studies have looked at securing the CAN and at intrusion detection methods so that attacks can be quickly identified. The CAN has qualities that distinguish it from other computer networks, while the nature of car production and usage also provide challenges. Thus attach detection methods employed for other networks lack appropriateness for the CAN. This paper surveys the methods that have been investigated for CAN intrusion detection, and considers their implications in terms of practicability and requirements. Consequent developments that will be needed for implementation and research are suggested.",

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Towards Viable Intrusion Detection Methods For The Automotive Controller Area Network

Abstract

Conference

Keywords

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